In a common image display system, e.g., a television (TV), a digital camera (DC) or a personal computer, considering a sawtooth edge created due to noise interferences or a scaled-down image (e.g., when a high-resolution image is converted into a low-resolution image), a low-pass filter is implemented to improve its image quality. Generally speaking, the low-pass filter generates a filtered luminance/chrominance value of a pixel by weighted-averaging the luminance/chrominance value of the pixel and luminance/chrominance values of neighboring pixels. After the low-pass filtering, an image edge of the low-pass filtered image data is relatively smooth.
However, although the low-pass filtering can reduce the image noises and solve the problem of a sawtooth edge, the image edge meanwhile becomes blurred due to the low-pass filtering. Referring to FIG. 1, suppose that an original image frame comprises two neighboring areas 110 and 120 of different colors (e.g., the color in the area 110 is yellow and the color in the area 120 is blue), and between the two neighboring areas 110 and 120 is an edge 102. After a low-pass filtering, the edge 102 becomes blurred, and thus a blurred area 104 is formed in the vicinity of the edge 102. Chrominance changes of the area 102 are illustrated with reference to chrominance values Cb and Cr at the bottom of FIG. 1. Solid lines are distributions of chrominance values Cb and Cr of the original image frame, and dashed lines are distributions of chrominance values Cb and Cr of the area 104 after the low-pass filtering. As observed from the values Cb and Cr in FIG. 1, pixels in the area 104 have different colors.
In order to solve the problem of edge blur of the low-pass filtered image frame, a common approach is that the image display system performs edge enhancement on the low-pass filtered image frame. Following description is given with reference to FIG. 1 and FIG. 2. FIG. 2 shows a schematic diagram of a conventional method for solving the problem of edge blur of an image. CPi, CP1, and CPr in FIG. 2 are respectively coordinate points of pixels Pi, P1, and Pr in color coordinate axes in FIG. 1. For the conventional method, the chrominance values Cb and Cr of the pixel Pi in the blurred area 104 are adjusted to the chrominance values Cb and Cr of the pixel P1 or Pr to solve the problem of edge blur. For example, the image display system determines whether the value Cb of the pixel Pi is more approximate to the value Cb of the pixel P1 or the pixel Pr, and defines the more approximate value Cb (i.e., the value Cb of the pixel P1 or the pixel Pr) as an adjusted value Cb of the pixel Pi. Likewise, the image display system determines whether the value Cr of the pixel Pi is more approximate to the value Cr of the pixel P1 or the pixel Pr, and defines the more approximate value Cr (i.e., the value Cb of the pixel P1 or the pixel Pr) as an adjusted value Cr of the pixel P. An object of the foregoing method is to adjust the color of the area 104 to the color of the area 110 or the area 120, so as to solve the problem of edge blur. However, with respect to a special situation in FIG. 2, the foregoing method may form another color at the image edge of the image frame to create image frame distortion. Referring to FIG. 2, since the value Cb of the pixel Pi is more approximate to the value Cb of the pixel P1, the adjusted value Cb of the pixel Pi is equal to the value Cb of the pixel P1; and since the value Cr of the pixel Pi is more approximate to the value Cr of the pixel Pr, the adjusted value Cr of the pixel Pi is equal to the value Cr of the pixel Pr. As illustrated in FIG. 2, the coordinate point CPi—adj of an adjusted chrominance value of the pixel Pi in the color coordinate axes represents another color, which is different from a color (represented by a coordinate CP1) of the area 110 and a color (represented by a coordinate CPr) of the area 120, and thus image quality of the image frame is deteriorated as the image frame distortion is created.